2 datasets found
  1. NIOSH Anthropometric Data and ISO Digital Headforms

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Nov 19, 2024
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    data.cdc.gov (2024). NIOSH Anthropometric Data and ISO Digital Headforms [Dataset]. https://healthdata.gov/dataset/NIOSH-Anthropometric-Data-and-ISO-Digital-Headform/fw2n-p797
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    application/rdfxml, tsv, application/rssxml, csv, json, xmlAvailable download formats
    Dataset updated
    Nov 19, 2024
    Dataset provided by
    data.cdc.gov
    Description

    In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a nationwide anthropometric survey of 3,997 subjects. The resulting head and face measurements were used to develop an anthropometric database detailing the face size distributions of respirator users using both traditional measurement methods and three-dimensional (3D) scanning systems. This database was used to establish fit test panels to be incorporated into NIOSH respirator certification and international standards. One of the panels developed, called the principal component analysis (PCA) panel, uses the first two principal components obtained from a set of 10 facial dimensions (age and race adjusted) and divides user population into five face-size categories. These 10 dimensions are associated with respirator fit and leakage and can predict the remaining face dimensions as well. Respirators designed to fit these panels are expected to accommodate more than 95% of the current U.S. civilian workers.

    From the 3,997 subje

  2. Z

    Supplementary data to the paper: Automatic Extraction of Anthropometric...

    • data.niaid.nih.gov
    Updated Jul 12, 2024
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    Avanzini, Federico (2024). Supplementary data to the paper: Automatic Extraction of Anthropometric Features for the Individualization of the Pinna-Related Transfer Function in the Median Plane [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7982266
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    Dataset updated
    Jul 12, 2024
    Dataset provided by
    Fantini, Davide
    Ntalampiras, Stavros
    PRESTI, GIORGIO
    Avanzini, Federico
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Supplementary research data to the paper (rejected):

    Davide Fantini, Federico Avanzini, Stavros Ntalampiras and Giorgio Presti (2023) "Automatic Extraction of Anthropometric Features for the Individualization of the Pinna-Related Transfer Function in the Median Plane"

    The repository includes the research data generated and analyzed in the abovementioned paper describing a method for PRTF individualization. In particular, the following data are included:

    README.md: instructions for the data

    pinna_range_img.mat: pinna range images extracted from the 3D head meshes of the HUTUBS dataset

    landmarks.mat: landmarks coordinates both manually annotated and automatically placed with ASM

    anthropometry.mat: anthropometric parameters automatically extracted from both manually annotated and ASM-fitted landmarks

    img_features.mat: image features pinna cavities extracted from both manually annotated and ASM-fitted landmarks

    grnn_models.mat: Generalized Regression Neural Network (GRNN) models trained from both HUTUBS anthropometry and the proposed pinna features

    predicted_dtf.mat: Directional Transfer Function (DTF) sets predicted from both HUTUBS anthropometry and the proposed pinna features

    anthropometry_documentation.pdf: documentation of the pinna anthropometric parameters

    auditory_model_complete_elevation_range.pdf: auditory model evaluation in the complete elevation range

    The data are provided in the Matlab file format MAT. Nevertheless, the MAT files can be read with other programming languages, such as Python (scipy.io.loadmat).

    A GitHub repository to automatically extract the pinna landmarks and features as described in the paper is available here.

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data.cdc.gov (2024). NIOSH Anthropometric Data and ISO Digital Headforms [Dataset]. https://healthdata.gov/dataset/NIOSH-Anthropometric-Data-and-ISO-Digital-Headform/fw2n-p797
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NIOSH Anthropometric Data and ISO Digital Headforms

Explore at:
27 scholarly articles cite this dataset (View in Google Scholar)
application/rdfxml, tsv, application/rssxml, csv, json, xmlAvailable download formats
Dataset updated
Nov 19, 2024
Dataset provided by
data.cdc.gov
Description

In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a nationwide anthropometric survey of 3,997 subjects. The resulting head and face measurements were used to develop an anthropometric database detailing the face size distributions of respirator users using both traditional measurement methods and three-dimensional (3D) scanning systems. This database was used to establish fit test panels to be incorporated into NIOSH respirator certification and international standards. One of the panels developed, called the principal component analysis (PCA) panel, uses the first two principal components obtained from a set of 10 facial dimensions (age and race adjusted) and divides user population into five face-size categories. These 10 dimensions are associated with respirator fit and leakage and can predict the remaining face dimensions as well. Respirators designed to fit these panels are expected to accommodate more than 95% of the current U.S. civilian workers.

From the 3,997 subje

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